Senior Machine Learning Engineer

As a Senior Machine Learning Engineer, you will be responsible for designing, developing, and deploying cutting-edge models for end-to-end content generation, including AI-driven image/video generation, lip syncing, and multimodal AI systems. You will work on the latest advancements in deep generative modeling to create highly realistic and controllable AI-generated content. - **Research and Develop**: - Design and implement state-of-the-art generative models, including Diffusion Models, 3D VAEs, and GANs for AI-powered media synthesis. - **End-to-End Content Generation**: - Build and optimize AI pipelines for high-fidelity image/video generation and lip syncing using diffusion and autoencoder models. - **Speech and Video Synchronization**: - Develop advanced lip-syncing and multimodal generation models that integrate speech, video, and facial animation for hyper-realistic AI-driven content. - **Real-Time AI Systems**: - Implement and optimize models for real-time content generation and interactive AI applications using efficient model architectures and acceleration techniques. - **Scaling and Production Deployment**: - Work closely with software engineers to deploy models efficiently on cloud-based architectures (AWS, GCP, or Azure). - **Collaboration and Research**: - Stay ahead of the latest trends in deep generative models, diffusion models, and transformer-based vision systems to enhance AI-generated content quality. - **Experimentation and Validation**: - Design and conduct experiments to evaluate model performance, improve fidelity, realism, and computational efficiency, and refine model architectures. - **Code Quality and Best Practices**: - Participate in code reviews, improve model efficiency, and document research findings to enhance team knowledge-sharing and product development. Qualifications: - Bachelor's or Master's degree in Computer Science, Machine Learning, or a related field. - 3+ years of experience working with deep generative models, including Diffusion Models, 3D VAEs, GANs, and autoregressive models. - Strong proficiency in Python and deep learning frameworks such as PyTorch. - Expertise in multi-modal AI, text-to-image, image-to-video generation, and audio to lip sync. - Strong understanding of machine learning principles and statistical methods. - Good to have experience in real-time inference optimization, cloud deployment, and distributed training. - Strong problem-solving abilities and a research-oriented mindset to stay updated with the latest AI advancements.,